AI Data & Knowledge Engineer

What you'll do

• Develop RAG-ready pipelines and semantic, hybrid-search, and knowledge-graph layers for AI applications.
• Operate distributed data systems and synchronize structured and unstructured data while ensuring quality and governance.
• Partner with Analytics, Data Science, and business teams to deliver reliable knowledge layers and document data models and processes.

What they ask for

• Experience designing knowledge layers for AI systems, including knowledge graphs, RAG pipelines, and vector databases.
• Experience modeling enterprise knowledge and metadata in semantic layers.
• 5+ years of experience designing, building, and maintaining scalable data solutions for large-scale analytics.
• Proficiency in SQL and programming languages such as Python, Java, or R; experience with cloud databases, distributed processing, modern data-stack tools, and a cloud platform.

Nice to have

• Experience with ETL tools, API integration, ontology-based semantic layers, or LLM evaluation and AI quality tooling.
• Experience with data governance and observability tools, such as DataHub or Collibra.

Pay

$149,200 and $249,000 USD base salary

Tools

SQL, Snowflake, Redshift, Databricks, Python, Java, R, Apache Airflow

AI focus

Build data infrastructure for AIML initiatives, including RAG pipelines, knowledge layers, semantic and hybrid search, and data-quality processes for model training and deployment.